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Data Management Plan

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By Augustine Emmanuel
3 min read

Drafting Your Data Management Plan (DMP)

A Data Management Plan (DMP) is a formal document outlining how research data will be handled both during the research process and after the project is completed. It details how data will be collected, processed, stored, shared, and preserved, ensuring that data remains accessible and usable over time. A well-crafted DMP is essential for promoting transparency, reproducibility, and the longevity of research data.

Importance of a DMP

Creating a DMP is not just about ticking a box for funders. It plays a crucial role in the research process, serving multiple purposes:

  • Ensures Data Quality: By clearly defining roles and responsibilities, a DMP promotes accountability and ensures that the data collected is accurate, well-documented, and securely stored.

  • Facilitates Data Sharing: A DMP outlines how and when data will be shared, fostering collaboration and enabling other researchers to build on your work.

  • Supports Reproducibility: Properly managed data enhances the reproducibility of your research by making it easier for others to validate and replicate your findings.

  • Preserves Research Legacy: A DMP ensures that your data is preserved for long-term access, safeguarding it from being lost or becoming obsolete.

  • Compliance with Legal and Ethical Standards: It helps you address privacy concerns, intellectual property rights, and ethical issues, ensuring compliance with regulations and institutional guidelines.

  • Mitigates Risks: With a clear plan for data management, you reduce the risks associated with data loss, corruption, or breaches of confidentiality.

When planning a DMP, it is expected that it highlights the following:

Roles and Responsibilities

Define who will be responsible for managing, sharing, and preserving your data throughout the project. Be specific about who is in charge of which tasks, and ensure there is a plan in place for continuity in case of personnel changes.

Example Text:

  • “The project will assign a certified data manager to act as steward for the data while they are being collected, processed, and analysed.”
  • “Day-to-day quality assessment will be handled by the Lab Director under the oversight of the Project Director.”

Types of Data

Provide a brief description of the data you will be generating, including any estimates on the amount and type of data. Clarify whether the data will be new, or if you will be integrating existing data sources.

Example Text:

  • “Data will be collected and stored in two relational databases.”
  • “This project will generate public-use nationally representative survey data covering Americans’ political values and opinions.”

Data Formats and Metadata

Specify the file formats you will use for your data, as well as how you will capture any metadata that makes your data meaningful to others. It’s important to detail how files will be named and versioned.

Example Text:

  • “Research data will be stored in CSV format, and metadata will be generated using the Dublin Core standard.”
  • “Data will conform to best practices from the X community and will be versioned using Git.”

Access, Sharing, and Privacy

Explain how and when you will share the data, including any potential restrictions due to ethics, privacy, or intellectual property. Clarify who will have access and under what conditions.

Example Text:

  • “Data will be posted on a project website within three months of the grant’s conclusion.”
  • “Data will be available to the public through X repository after an embargo period of six months.”

Data Storage and Preservation

Describe how long your data will be stored and the strategy for its long-term preservation. This may involve detailing the role of a repository or institutional archive in safeguarding your data over time.

Example Text:

  • “Research data will be deposited with the institutional repository to ensure long-term access.”
  • “To ensure future access, data will be stored and migrated to new formats as needed by the repository.”

Conclusion

A Data Management Plan is more than just a requirement for funding applications; it is a vital component of the research process. By ensuring data quality, facilitating sharing, and safeguarding data for future use, a well-crafted DMP contributes to the sustainability and impact of your research. Use the DMPTool to create your DMP, making sure it reflects the unique needs of your project and adheres to any specific guidelines from your funding agency.

Remember, your DMP should evolve as your project progresses, and regular updates will help keep your data management practices on track.

RESEARCH, DATA MANAGEMENT
data management research planning
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